Structural plasticity of olfactory neuropils in relation to insect diapause

Two distinct aphid diapause strategies: slow development or development arrest

Aphids adapt to unfavourable environmental conditions, such as low temperatures in winter, by laying diapausing eggs that overwinter. Diapause is a stress-resistant and developmentally arrested stage that can be adopted in order to increase the chance of survival in adverse environmental conditions. The diapause process of aphids is still very poorly understood. We followed the development of two species of aphids, Brachycorynella asparagi and Appendiseta robiniae, using the immunostained embryos of the aphids to identify mitotic cell divisions. Two different models of aphid diapause were demonstrated for the first time. In the first strategy, the embryo developed continuously during winter diapause, while in the second case, there was an embryonic arrest. The possibility of slow development of the whole body during diapause is a characteristic feature of aphids. The link to the plant's phenology appears to be a key factor in determining the diapause strategy in aphids.

Seasonal variations of serotonin in the visual system of an ant revealed by immunofluorescence and a machine learning approach

Hibernation, as an adaptation to seasonal environmental changes in temperate or boreal regions, has profound effects on mammalian brains. Social insects of temperate regions hibernate as well, but despite abundant knowledge on structural and functional plasticity in insect brains, the question of how seasonal activity variations affect insect central nervous systems has not yet been thoroughly addressed. Here, we studied potential variations of serotonin-immunoreactivity in visual information processing centres in the brain of the long-lived ant species Lasius niger. Quantitative immunofluorescence analysis revealed stronger serotonergic signals in the lamina and medulla of the optic lobes of wild or active laboratory workers than in hibernating animals. Instead of statistical inference by testing, differentiability of seasonal serotonin-immunoreactivity was confirmed by a machine learning analysis using convolutional artificial neuronal networks (ANNs) with the digital immunofluorescence images as input information. Machine learning models revealed additional differences in the third visual processing centre, the lobula. We further investigated these results by gradient-weighted class activation mapping. We conclude that seasonal activity variations are represented in the ant brain, and that machine learning by ANNs can contribute to the discovery of such variations.

Chromosome Level Assembly of the Comma Butterfly (Polygonia c-album)

The comma butterfly (Polygonia c-album, Nymphalidae, Lepidoptera) is a model insect species, most notably in the study of phenotypic plasticity and plant-insect coevolutionary interactions. In order to facilitate the integration of genomic tools with a diverse body of ecological and evolutionary research, we assembled the genome of a Swedish comma using 10X sequencing, scaffolding with matepair data, genome polishing, and assignment to linkage groups using a high-density linkage map. The resulting genome is 373 Mb in size, with a scaffold N50 of 11.7 Mb and contig N50 of 11,2Mb. The genome contained 90.1% of single-copy Lepidopteran orthologs in a BUSCO analysis of 5,286 genes. A total of 21,004 gene-models were annotated on the genome using RNA-Seq data from larval and adult tissue in combination with proteins from the Arthropoda database, resulting in a high-quality annotation for which functional annotations were generated. We further documented the quality of the chromosomal assembly via synteny assessment with Melitaea cinxia. The resulting annotated, chromosome-level genome will provide an important resource for investigating coevolutionary dynamics and comparative analyses in Lepidoptera.